Abstract Background Tick-borne encephalitis virus (TBEV) is a significant threat to human health. The virus causes potentially fatal disease of the central nervous system (CNS), for which no treatments are available. TBEV infected individuals display a wide spectrum of neuronal disease, the determinants of which are undefined. Changes to host metabolism and virus-induced immunity have been postulated to contribute to the neuronal damage observed in infected individuals. In this study, we evaluated the cytokine, chemokine, and metabolic alterations in the cerebrospinal fluid (CSF) of symptomatic patients infected with TBEV presenting with meningitis or encephalitis. Our aim was to investigate the host immune and metabolic responses associated with specific TBEV infectious outcomes. Methods CSF samples of patients with meningitis (n = 27) or encephalitis (n = 25) were obtained upon consent from individuals hospitalised with confirmed TBEV infection in Brno. CSF from uninfected control patients was also collected for comparison (n = 12). A multiplex bead-based system was used to measure the levels of pro-inflammatory cytokines and chemokines. Untargeted metabolomics followed by bioinformatics and integrative omics were used to profile the levels of metabolites in the CSF. Human motor neurons (hMNs) were differentiated from induced pluripotent stem cells (iPSCs) and infected with the highly pathogenic TBEV-Hypr strain to profile the role(s) of identified metabolites during the virus lifecycle. Virus infection was quantified via plaque assay. Results Significant differences in proinflammatory cytokines (IFN-α2, TSLP, IL-1α, IL-1β, GM-CSF, IL-12p40, IL-15, and IL-18) and chemokines (IL-8, CCL20, and CXCL11) were detected between neurological-TBEV and control patients. A total of 32 CSF metabolites differed in TBE patients with meningitis and encephalitis. CSF S-Adenosylmethionine (SAM), Fructose 1,6-bisphosphate (FBP1) and Phosphoenolpyruvic acid (PEP) levels were 2.4-fold (range ≥ 2.3-≥3.2) higher in encephalitis patients compared to the meningitis group. CSF urocanic acid levels were significantly lower in patients with encephalitis compared to those with meningitis (p = 0.012209). Follow-up analyses showed fluctuations in the levels of O-phosphoethanolamine, succinic acid, and L-proline in the encephalitis group, and pyruvic acid in the meningitis group. TBEV-infection of hMNs increased the production of SAM, FBP1 and PEP in a time-dependent manner. Depletion of the metabolites with characterised pharmacological inhibitors led to a concentration-dependent attenuation of virus growth, validating the identified changes as key mediators of TBEV infection. Conclusions Our findings reveal that the neurological disease outcome of TBEV infection is associated with specific and dynamic metabolic signatures in the cerebrospinal fluid. We describe a new in vitro model for in-depth studies of TBEV-induced neuropathogenesis, in which the depletion of identified metabolites limits virus infection. Collectively, this reveals new biomarkers that can differentiate and predict TBEV-associated neurological disease. Additionally, we have identified novel therapeutic targets with the potential to significantly improve patient outcomes and deepen our understanding of TBEV pathogenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-025-03478-4. Keywords: Tick-borne encephalitis virus, Cerebrospinal fluid, Human motor neurons, Metabolomics, Pro-inflammatory cytokines, Chemokines, Neuroinflammation Background Tick-borne encephalitis virus (TBEV) is an Ixodes spp.-tick-borne orthoflavivirus with the potential to cause human epidemics of severe and fatal encephalitis [[44]1–[45]3]. TBEV is endemic in Asia (including northern China and Japan) [[46]4, [47]5] and in 27 countries in Europe [[48]1, [49]6–[50]8], including recent detection in the UK [[51]9], Netherlands [[52]10] and North Africa [[53]11]. TBEV is recognised as a global pathogen of concern and is highlighted in the World Health Organisation (WHO) global vector control response 2017–2030. TBEV is classified into five subtypes: Baikalian, Himalayan, European, Siberian, and Far Eastern [[54]12]. TBEV primarily infects neurons and is associated with CNS pathology [[55]3, [56]13–[57]16]. Human TBEV is acquired through the bite of an infected tick or through the consumption of unpasteurized milk or milk products from infected animals (alimentary transmission). TBEV associated disease follows a biphasic course; Phase 1 (viraemic) is characterised by non-specific febrile illness (flu-like symptoms), lasting up to 7 days; Phase 2 (∼ 30% of those infected) involves neurological disease (tick-borne encephalitis [TBE]) [[58]17–[59]20] that manifests as a range of nonspecific symptoms including meningitis, encephalitis, loss of coordination, difficulties with speech, limb weakness, seizures, fever and headaches [[60]2, [61]17, [62]20–[63]24]. Severe TBEV cases are associated with cytopenia, elevated serum C-reactive protein (CRP) levels in the blood, serum anti-TBEV IgG antibodies [[64]2, [65]17] and low levels of neutralizing antibodies in both the serum and CSF [[66]22]. Neurological manifestations are less well understood, with no specific CNS biomarkers identified. The clinical course and outcome of TBEV infection is dictated by the site of infection, host immune response, genetics, virus subtype/strain and age [[67]2, [68]20, [69]25]. The incubation period ranges from 7 to 14 days, but shorter periods (3–4 days) have been reported for alimentary infections [[70]8, [71]26, [72]27]. Severe forms of higher susceptibility have been described in adults (> 60 years of age) with those aged over 40 years at an increased risk of developing encephalitis [[73]2, [74]17, [75]21]. Approximately 40–50% of adults (age ranged 16–76) develop post-encephalitic syndrome [[76]28] that can last up to 18 months after the onset of the acute (first phase) illness. Over 10% of those infected show permanent sequelae, including spinal nerve paresis, dysarthria and severe mental disorders [[77]28–[78]30]. Age-dependent (range 15–78) long-term or permanent neuropsychiatric disorders are observed in ∼ 20% of those infected [[79]13]. Given the complexity of disease presentation, the discovery of biomarkers that can predict disease progression hold great value for TBEV studies. Metabolomic analysis of the cerebrospinal fluid (CSF) has increased knowledge of the naturally occurring processes of virus infections including for COVID-19 [[80]31], West Nile [[81]32] and dengue fever [[82]33] and can reflect disease-associated CNS pathology [[83]31, [84]34–[85]36]. Metabolism is also closely linked to the immune response to virus infection, with succinate, glucose and specific lipids identified as proinflammatory (e.g., IL-1β) and itaconate an anti-inflammatory (negative regulator of IL-6 and IL-12) [[86]31, [87]37]. In this study, to address knowledge gaps regarding the outcome of TBEV-associated disease, we characterised key changes in metabolites, proinflammatory cytokines and chemokine levels in the CSF samples of hospitalised TBEV patients. As the patient cohorts were documented for TBEV-associated neurological outcomes, this allowed us to identify key CSF metabolites related to disease severity that could be used to predict the course of TBEV infection. A new physiological in vitro model of TBEV-infection was also developed using human iPSC-derived motor neurons to confirm the role of identified metabolites during the TBEV-lifecycle. Herein, we report the identification of inflammatory and metabolic markers for the diagnosis of TBEV in CSF samples that can stratify patients with encephalitis and meningitis. Materials and methods Clinical information and sample collection Cerebrospinal fluid (CSF) samples were obtained upon consent from individuals hospitalised with confirmed TBEV (strain Hypr) or with non-TBEV in Brno (approval no. 103/19), Czech Republic. Samples were from the recent seasonal TBEV outbreak (2020–2023). Protocols were approved by the ethics committee of the University Hospital in Brno (date of approval: June 27, 2018). Clinical data were obtained from hospitalised CNS-TBEV patients at the treating hospital. TBEV clinical tests were conducted using EIA TBE Virus IgG (TBG096) and EIA TBE Virus IgM (TBM096) kits from TestLine Clinical Diagnostics. Severity of disease was evaluated according to the following scale: [[88]1] Mild, flu-like symptoms with meningeal irritation defined as meningitis, characterised by fever, fatigue, nausea, headache, back pain, arthralgia/myalgia and neck or back stiffness; [[89]2] Moderate, previous symptoms together with tremor, vertigo, somnolence and photophobia defined as meningoencephalitis; [[90]3] Severe, prolonged neurological consequences including ataxia, titubation, altered mental status, memory loss, quantitative disturbance of consciousness, and palsy revealed as encephalitis, encephalomyelitis, or encephalomyeloradiculitis. Samples were collected through lumbar puncture (LP) and stored at − 80 °C prior to analysis. A total of 64 participants were enrolled, including 25 diagnosed with encephalitis, 27 with meningitis (Supplementary Tables [91]S1 and [92]S2), and 12 with non-TBEV associated illness (control group). The control group did not present any neurological disease and were not diagnosed with known virological infections. Samples were obtained at the time of hospitalisation during the second phase of the disease. Four-month follow-up samples were collected from 10 cohorts, comprising 6 individuals diagnosed with encephalitis and 4 with meningitis. Patient demographics, clinical outcomes, immune responses (cytokines/chemokines) and metabolomics of CSF samples were analysed to fully profile the host response to TBEV infection. RNA extraction Total RNA was isolated using ZymoBIOMICS DNA/RNA Miniprep Kit (ZYMO RESEARCH, R2002), accordingly to the manufacturers protocol. RNA was eluted, quantified (NanoDrop Microvolume Spectrophotometers, Thermo Fisher Scientific) and stored at − 80 °C. RT-PCR RT–PCRs were performed as previously described [[93]7, [94]38]. Briefly, One-Step TB Green PrimeScript RT-PCR Kit II (Takara, RR086A) was used. A total of 1 µg of total RNA was purified from the CSF. Analysis was performed using primers at a concentration of 0.8 µM in a final volume of 25 µl. One step RT-PCR was performed at 42 °C for 5 min, followed by denaturation (95 °C/5 secs) and 40 cycles of amplification with denaturation at 95 °C for 5 s and annealing at 60 °C for 30 s. Ct value ≥ 40 was considered as a cut-off for no virus detection. Statistical analysis was performed using GraphPad Prism 9 software. Chemokine measurements in CSF samples from TBEV-patients and controls The levels of 13 proinflammatory chemokines in the CSF (25 µL) were simultaneously measured using LEGENDplex™ HU Proinflam. Chemokine Panels (740984; BioLegend), according to the manufacturer’s instructions. Analysis was performed on a Cytoflex machine. The human proinflammatory chemokine panel included MCP-1 (CCL2), RANTES (CCL5), IP-10 (CXCL10), Eotaxin (CCL11), TARC (CCL17), MIP-1α (CCL3), MIP-1β (CCL4), MIG (CXCL9), MIP-3α (CCL20), ENA-78 (CXCL5), GROα (CXCL1), I-TAC (CXCL11) and IL-8 (CXCL8). Data were analysed using BioLegend’s LEGENDplex™ (LEGENDplex™ Software (biolegend.com) or FlowJo (BD) (FlowJo, LLC). Statistical analysis was performed using GraphPad Prism 9 software. Cytokine measurements in CSF samples from TBEV-patients and controls The levels of 13 cytokines in the CSF were measured using the LEGENDplex™ Human Cytokine Panel (741377; BioLegend) on a Cytoflex machine. The human proinflammatory chemokine panel included IFN-α2, TSLP, IL-1α, IL-1β, GM-CSF, IL-11, IL-12p40, IL-12p70, IL-15, IL-18, IL-23, IL-27 and IL-33. Data were analysed using BioLegend’s LEGENDplex™ (LEGENDplex™ Software (biolegend.com) or FlowJo (BD) (FlowJo, LLC). Statistical analysis was performed using GraphPad Prism 9 software. Untargeted polar metabolomic profiling for CSF samples A total of 50 µL of CSF was mixed in 80% methanol (Sigma) on dry ice and incubated at − 80 °C for 4 h. CSF were centrifuged at 14,000 rfc for 20 min at 4 °C. Supernatants were extracted and stored at − 80 °C. The Weill Cornell Medicine Meyer Cancer Center Proteomics & Metabolomics Core Facility performed hydrophilic interaction liquid chromatography-mass spectrometry (LC-MS) for the relative quantification of polar metabolite profiles. Metabolites were measured on a Q Exactive Orbitrap mass spectrometer, coupled to a Vanquish UPLC system using an Ion Max ion source with a HESI II probe (Thermo Scientific). A Sequant ZIC-pHILIC column (2.1 mm i.d. × 150 mm, particle size of 5 μm, Millipore Sigma) was used for separation. MS data were processed using XCalibur 4.1 (Thermo Scientific) to obtain metabolite signal intensities for relative quantitation. For untargeted metabolomics, metabolites were identified by mass by matching of the MS signal to metabolites in the HMDB database. If multiple metabolites were matched to a specific MS signal, all were grouped into a single identification and ordered based on the number of references included